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In crises such as the coronavirus disease 2019 (COVID-19) pandemic, governments need to act in time to lead citizens toward rational reactions and disclose information effectively to the public. This paper aims to understand the content published by the government and identify how citizen engagement relates to content type and emotional valence.

The grounded theory approach was adopted and nine types of content posted by the government were observed. The data were obtained from “People's Daily”, an official Sina Weibo account representing the voice of the Chinese government, from January 3 to June 22 in 2020.

The analysis shows that information related to emotional support and social mobilization were the most reposted, while those mentioning immoral and illegal incidents were the most liked and commented. Also, it was found that positive posts tend to attract more likes, yet with fewer reposts than neutral posts.

The authors adopted thematic analysis and focused on the impact of post content and valence on user participation behavior. This study expands the existing literature. The government can improve crises management capability by learning about citizen engagement behaviors on social media.

Continuance usage of mobile applications (apps) has attracted much attention from scholars and enterprises, while the extant research mainly focuses on continuance intention. The inner effect mechanism of the characteristics of apps is still unclear. Under the tenet of continuance usage behaviour, through analysis of characteristics derived from online reviews, this paper aims to establish an effective model and discloses the commonalities and differences between two mainstream apps, which are entertainment and knowledge apps.

The authors collected reviews of TikTok and Zhihu, which are typical representatives of entertainment and knowledge apps, respectively, from 2018 to 2020. They then derive effect factors and establish the effect model using grounded theory. A deep comparison is then conducted. They analysed the similarities and differences in the general effect model, internal effect mechanism and detailed characteristics of the two types of apps.

Entertainment app and knowledge apps share the same general effect mechanism; that is, the effect chain of characteristics to perceived value then finally to continuance usage behaviour. However, obvious differences also exist in detailed and specific effects between the two apps.

The present research is among the first to have a deep analysis of the comparison of entertainment apps and knowledge apps under the context of continuance usage behaviour. The findings contribute to understanding continuance usage behaviours. Suggestions are proposed on how to promote apps, which may benefit app managers.